by Tobias Meyer, Thorben Kaul and Walter Sextro
Abstract:
Intelligent mechatronic systems other the possibility to adapt system behavior to current dependability. This can be used to assure reliability by controlling system behavior to reach a pre-defined lifetime. By using such closed loop control, the margin of error of useful lifetime of an individual system is lowered. It is also possible to change the pre-defined lifetime during operation, by adapting system behavior to derate component usage. When planning maintenance actions, the remaining useful lifetime of each individual system has to be taken into account. Usually, stochastic properties of a fleet of systems are analyzed to create maintenance plans. Among these, the main factor is the probability of an individual system to last until maintenance. If condition-based maintenance is used, this is updated for each individual system using available information about its current state. By lowering the margin of error of useful lifetime, which directly corresponds to the time until maintenance, extended maintenance periods are made possible. Also using reliability-adaptive operation, a reversal of degradation driven maintenance planning is possible where a maintenance plan is setup not only according to system properties, but mainly to requirements imposed by maintenance personnel or infrastructure. Each system then adapts its behavior accordingly and fails according to the maintenance plan, making better use of maintenance personnel and system capabilities at the same time. In this contribution, the potential of maintenance plan driven system behavior adaptation is shown. A model including adaptation process and maintenance actions is simulated over full system lifetime to assess the advantages gained.
Reference:
Meyer, T.; Kaul, T.; Sextro, W.: Advantages of reliability-adaptive system operation for maintenance planning. Proceedings of the 9th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes, 2015. (Preprint: http://www.tobi-meyer.de/Meyer2015a.pdf)
Bibtex Entry:
@INPROCEEDINGS{Meyer2015a,
howpublished = {Conference Proceedings},
author = {Tobias Meyer AND Thorben Kaul AND Walter Sextro},
title = {Advantages of reliability-adaptive system operation for maintenance
planning},
booktitle = {Proceedings of the 9th IFAC Symposium on Fault Detection, Supervision
and Safety for Technical Processes},
year = {2015},
pages = {940-945},
abstract = {Intelligent mechatronic systems other the possibility to adapt system
behavior to current dependability. This can be used to assure reliability
by controlling system behavior to reach a pre-defined lifetime. By
using such closed loop control, the margin of error of useful lifetime
of an individual system is lowered. It is also possible to change
the pre-defined lifetime during operation, by adapting system behavior
to derate component usage. When planning maintenance actions, the
remaining useful lifetime of each individual system has to be taken
into account. Usually, stochastic properties of a fleet of systems
are analyzed to create maintenance plans. Among these, the main factor
is the probability of an individual system to last until maintenance.
If condition-based maintenance is used, this is updated for each
individual system using available information about its current state.
By lowering the margin of error of useful lifetime, which directly
corresponds to the time until maintenance, extended maintenance periods
are made possible. Also using reliability-adaptive operation, a reversal
of degradation driven maintenance planning is possible where a maintenance
plan is setup not only according to system properties, but mainly
to requirements imposed by maintenance personnel or infrastructure.
Each system then adapts its behavior accordingly and fails according
to the maintenance plan, making better use of maintenance personnel
and system capabilities at the same time. In this contribution, the
potential of maintenance plan driven system behavior adaptation is
shown. A model including adaptation process and maintenance actions
is simulated over full system lifetime to assess the advantages gained.},
note = {Preprint: \url{http://www.tobi-meyer.de/Meyer2015a.pdf}},
doi = {10.1016/j.ifacol.2015.09.647},
keywords = {Adaptive systems, Reliability analysis, Availability, Adaptive control,
Maintenance, Self-optimizing systems, Self-optimizing control, Stochastic
Petri-nets}
}